Advocate Reward Email Analyticsrticle

Samantha Brown Updated by Samantha Brown

Overview

The Advocate Reward Email Analytics dashboard helps you measure the performance of the emails that are sent to Advocates when they've earned a referral reward. These metrics allow you to understand how effectively your emails are driving clicks, purchases, and referral revenue.

This dashboard is located under Analytics → Email Metrics and provides both high-level KPIs and trend visualizations over a selected time range.

Key Metrics

Each Advocate Reward Email is tracked across several important performance indicators:

  1. Emails Sent: The total number of reward-related emails delivered to advocates.
  2. Unique Opens: The number of distinct recipients who opened the email at least once
    1. Key Metric: Unique Opens ÷ Emails Sent
    2. Use Case: A strong open rate (e.g., 84.68%) indicates that subject lines are resonating with recipients.
  3. Total Clicks: The total number of times links in the email were clicked (including multiple clicks by the same user)
    1. Key Metric: Click Rate = Total Clicks ÷ Unique Opens
    2. Use Case: Helps measure the effectiveness of email content and calls to action
  4. Unique Clicks: The number of individual recipients who clicked at least once.
    1. Use Case: Provides a clearer picture of actual audience engagement beyond total click volume.
  5. Purchases: The total number of completed purchases attributed to clicks from the advocate reward email.
    1. The total number of completed purchases attributed to clicks from the advocate reward email.
  6. Referral Revenue: The total revenue generated from purchases initiated by recipients of the reward email.

Data Visualization

Time-Series Graph

The bottom section of the dashboard displays a line graph showing trends for:

  • Emails Sent (dark blue)
  • Unique Opens (light blue)
  • Clicks (orange)

This visualization allows you to:

Identify spikes in engagement on specific dates.

  • Compare performance between opens and clicks.
  • Detect patterns (e.g., weekends, campaign launches, or promotions) that influence results.

How did we do?

Loyalty Email Analytics

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